How do you build a new team, like the Atlanta United, from the ground up? Check out this new Fanalytics episode where we sit with the team’s Head of Technical Recruitment & Performance Analysis @lucyrushton12! https://t.co/rVvlfnnJbg
@ATLUTD #atlantaunited #atlunitedfc pic.twitter.com/uz6ucOQy5y
— Emory MAC (@Emory_MAC) June 13, 2019
How do you build a new team, like the Atlanta United, from the ground up?
In this Fanalytics episode we meet Atlanta United’s Lucy Rushton. As the team’s Head of Technical Recruitment and Performance Analysis, she provides analytics, data and insights that help the team build their roster. In the conversation with Lucy we talk about two types of analyses. One part involves the subjective analysis which is watching the players on the field. The other part is the objective analysis which involves data and statistics, emotion is taken out of the analysis. Rushton says it’s important to get a balance between the two in order to drive a successful department.
So what’s the game plan when searching for players for the team? Rushton says to get data and find players that fit in with the club philosophy and playing styles. Styles include players who have fast attacking skills, can entertain, athleticism, and speed. You also have to ask, what are the key attributes of a player for the position they look for? How much do these players cost?
When it comes to statistical forecasting, how much of that do decision-makers want to see? They want to see the insights not the models.
What’s next for Atlanta United? The head scout says the goal is to get better, get another chance to play in the CONCACAF Champions League, and growth in analysis.
In the second half of the episode, we talk about some of the larger lessons related to performing and presenting analytics in any organization. Analytics is seldom a magic bullet for any organizational challenge. More often, analytics informs rather than directs decisions.
Along these lines, we frame the interview with Lucy and the challenge of building a championship roster in terms of decision support realities such as biases in human decision making and the limitations of statistical models.
To listen to this podcast episode, click on the logo below.